azure-aigateway
Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.
- installs 8w
- 116,447
- 30-day movement
- starts with the next reading
- Related entries
- 1
- Connections
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This is a SKILL.md agent skill that guides an AI coding agent through configuring Azure API Management as an AI Gateway for AI models, MCP tools, and agents. It bundles reference material on policies, configuration patterns, troubleshooting, and SDK quick references for Content Safety (Python/TypeScript) and API Management (Python/.NET), and relies on the Azure CLI (az) for configuration and testing.
Reach for it when you need an agent to set up or govern an AI gateway on Azure APIM — backends, policies, caching, rate limits, or cost controls — without assembling the steps yourself.
Use it to
- Add an Azure OpenAI or AI Foundry model backend to APIM
- Apply LLM governance policies like token limits and content safety
- Set up semantic caching and load balancing
- Configure MCP rate limiting or convert an API to MCP
- Import an OpenAPI spec and test the AI gateway endpoint
For Developers and platform teams managing AI workloads on Azure APIM
- Host repository
- microsoft/azure-skills
- Version
- 3.2.1
- Installs, lifetime
- 579k
- Installs, 8 weeks
- 116k
- Compatible with
- Requires Azure CLI (az) for configuration and testing
- Licence
- MIT
- Host stars
- 1,486
- Host language
- Shell